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Learning without Teachers? A Randomized Experiment of a Mobile Phone-Based Adult Education Program in Los Angeles - Working Paper 368

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  • Christopher Ksoll, Janny Aker, Danielle Miller, Karla C. Perez-Mendoza, and Susan L. Smalley

Abstract

Over 755 million adults worldwide are unable to read and write in any language. Yet the widespread introduction of information and communication technology offers new opportunities to provide standardized distance education to underserved illiterate populations in both developed and developing countries. Using data from a randomized experiment of an innovative mobile phone-based adult education program (Cell-Ed) in Los Angeles, we find that the Cell-Ed program significantly increased students’ basic and broad reading scores, equivalent to a 2-4 year increase in reading levels over a four-month period. The program also increased participants’ self-esteem by 7 percent as compared with the comparison group. These results are robust to correcting for non-random attrition using a variety of non-parametric methods, including using the phase-in design to tighten the Lee bounds. Our results suggest that there is great scope for using information technology as a means of improving educational skills for illiterate adults.

Suggested Citation

  • Christopher Ksoll, Janny Aker, Danielle Miller, Karla C. Perez-Mendoza, and Susan L. Smalley, 2014. "Learning without Teachers? A Randomized Experiment of a Mobile Phone-Based Adult Education Program in Los Angeles - Working Paper 368," Working Papers 368, Center for Global Development.
    • Handle: RePEc:cgd:wpaper:368
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    References listed on IDEAS

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    1. repec:wbk:wboper:9767 is not listed on IDEAS
    2. Abhijit V. Banerjee & Shawn Cole & Esther Duflo & Leigh Linden, 2007. "Remedying Education: Evidence from Two Randomized Experiments in India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1235-1264.
    3. Tahir Andrabi & Jishnu Das & Asim Ijaz Khwaja & Tristan Zajonc, 2011. "Do Value-Added Estimates Add Value? Accounting for Learning Dynamics," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 29-54, July.
    4. Matthias Doepke & Michèle Tertilt, 2019. "Does female empowerment promote economic development?," Journal of Economic Growth, Springer, vol. 24(4), pages 309-343, December.
    5. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 1071-1102.
    6. Esther Duflo, 2012. "Women Empowerment and Economic Development," Journal of Economic Literature, American Economic Association, vol. 50(4), pages 1051-1079, December.
    7. Guido W. Imbens & Charles F. Manski, 2004. "Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 72(6), pages 1845-1857, November.
    8. repec:ucp:ecdecc:doi:10.1086/661219 is not listed on IDEAS
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    11. Nava Ashraf, 2009. "Spousal Control and Intra-household Decision Making: An Experimental Study in the Philippines," American Economic Review, American Economic Association, vol. 99(4), pages 1245-1277, September.
    12. Jenny C. Aker & Christopher Ksoll & Travis J. Lybbert, 2012. "Can Mobile Phones Improve Learning? Evidence from a Field Experiment in Niger," American Economic Journal: Applied Economics, American Economic Association, vol. 4(4), pages 94-120, October.
    13. Niels-Hugo Blunch & Claus C Pörtner, 2005. "Literacy, Skills and Welfare: Effects of Participation in Adult Literacy Programs," Working Papers UWEC-2005-23-FC, University of Washington, Department of Economics, revised Aug 2009.
    14. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    15. Rukmini Banerji & James Berry & Marc Shotland, 2017. "The Impact of Maternal Literacy and Participation Programs: Evidence from a Randomized Evaluation in India," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 303-337, October.
    16. repec:ucp:ecdecc:v:57:y:2008:i:1:p:1-30 is not listed on IDEAS
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    Cited by:

    1. Kaitlin Anderson & Gema Zamarro & Jennifer Steele & Trey Miller, 2021. "Comparing Performance of Methods to Deal With Differential Attrition in Randomized Experimental Evaluations," Evaluation Review, , vol. 45(1-2), pages 70-104, February.
    2. Aker, Jenny C. & Ksoll, Christopher, 2019. "Call me educated: Evidence from a mobile phone experiment in Niger✰," Economics of Education Review, Elsevier, vol. 72(C), pages 239-257.
    3. Milusheva,Sveta, 2020. "Using Mobile Phone Data to Reduce Spread of Disease," Policy Research Working Paper Series 9198, The World Bank.

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    More about this item

    Keywords

    education; communication technology; cell-ed;
    All these keywords.

    JEL classification:

    • D1 - Microeconomics - - Household Behavior
    • I2 - Health, Education, and Welfare - - Education
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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